Merge pull request #15 from ucsusa/nonrenewable

Adds coal, nuclear, and CCGT generators to the model

.gitignore

@@ -158,3 +158,7 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+
+# data folders that are too large to keep with the reports
+Electric_Retail_Service_Territories
+Electric__Power_Transmission_Lines

README.md

@@ -9,6 +9,9 @@ A model of the Illinois electricity system built with PyPSA.
 
 * git
 * Either `conda` or `mamba` installed
+
+> [!WARNING] 
+> Running `conda update --all` may downgrade `pypsa` to 0.25.x to accomodate an update to `pyomo`. This will break the code. After running update, run `conda update pypsa` to fix.
 
 1. Clone the repository
 

data/README.md

@@ -12,7 +12,7 @@ through the Homeland Infrastructure Foundation Level Database (HIFLD).
 
 Unfortunately, due to the size of the file, the data are not included in this repository. Data about the
 buses are imputed from the transmission line dataset. Users attempting to replicate this work should download
-the data to the folder `pypsa-illinois/data/transmission-lines` and unzip. `pypsa-illinois` expects a shapefile dataset
+the data to the folder `pypsa-illinois/data/transmission_lines` and unzip. `pypsa-illinois` expects a shapefile dataset
 called `pypsa-illinois/data/transmission_lines/Electric__Power_Transmission_Lines/Electric__Power_Transmission_Lines.shp`.
 
 #### [Download the data here](https://atlas.eia.gov/datasets/geoplatform::transmission-lines/about)
@@ -22,8 +22,8 @@ called `pypsa-illinois/data/transmission_lines/Electric__Power_Transmission_Line
 
 The data for electric service territories is also availabe through EIA and HIFLD. Similar to the transmission line data,
 there is no method for extracting the data programmatically. Users attempting to replicate this work should download
-the data to the folder `pypsa-illinois/data/service-territories` and unzip. `pypsa-illinois` expects a shapefile dataset
-called `pypsa-illinois/data/transmission_lines/Electric__Power_Transmission_Lines/Electric__Power_Transmission_Lines.shp`.
+the data to the folder `pypsa-illinois/data/spatial-data` and unzip. `pypsa-illinois` expects a shapefile dataset
+called `pypsa-illinois/data/spatial-data/Electric_Retail_Service_Territories/Electric_Retail_Service_Territories.shp`.
 
 #### [Download the data here](https://atlas.eia.gov/datasets/geoplatform::electric-retail-service-territories-2/about)
 
@@ -34,6 +34,8 @@ Solar and wind resource data are extracted from the National Solar Radiation Dat
 
 The data are extracted using functions in the file `functions/nrel_data_api.py`. These functions are deployed in the notebook `notebooks/nrel_data_download.ipynb`.
 
+See comments on the function `make_csv_url` in `nrel_data_api.py` regarding the NREL API key, which is needed for this function to work. [These instructions (for Windows)](https://medium.com/analytics-vidhya/hide-your-secret-keys-with-conda-1d22e42b82ed) can be used to add an API key to the conda environment.
+
 ### [NSRDB](https://nsrdb.nrel.gov/about/what-is-the-nsrdb)
 
 > The NSRDB (Sengupta et al., 2018) is a high temporal and spatial resolution dataset consisting of the three most widely used measurements of solar radiation—global horizontal, direct normal, and diffuse horizontal irradiance—as well as other meteorological data. The earlier versions of the NSRDB were modeled using cloud and weather information primarily collected at airports. An adequate number of locations and temporal and spatial scales were used to accurately represent regional solar radiation climates. More details on the NSRDB version history can be found here. The current NSRDB is modeled using the NREL’s Physical Solar Model (PSM) with inputs from multi-channel measurements obtained from the Geostationary Operational Environmental Satellite (GOES) of the National Oceanic and Atmospheric Administration (NOAA), the Interactive Multisensor Snow and Ice Mapping System (IMS) of the National Ice Center (NIC), and the Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), of the National Aeronautics and Space Administration (NASA). The PSM is a two-step physical modeling process, in which cloud and aerosol properties are derived, collected and resampled in the initial step and then fed as inputs into a radiative transfer model, the Fast All-sky Radiation Model for Solar applications (FARMS) (Xie et al., 2016), in the subsequent step. Using the FARMS with Narrowband Irradiances for Tilted surfaces (FARMS-NIT) (Xie and Sengupta, 2018; Xie et al., 2018; Xie et al., 2019), the NSRDB can also provide users with spectral-on-demand irradiances based on their selection of time, location, and PV orientation.

functions/nrel_data_api.py

@@ -10,12 +10,12 @@
 
 nrel_api_key = os.environ.get('NREL_API_KEY')
 
-personal_data = {'api_key':nrel_api_key,
+"""personal_data = {'api_key':nrel_api_key,
                  'name':'Samuel+G+Dotson',
                  'reason':'Research',
                  'affiliation':'Union+of+Concerned+Scientists',
                  'email':'[email protected]',
-                 'mailing_list':'false'}
+                 'mailing_list':'false'}"""
 
 parameters = {'lon':40.09,
               'lat':-88.26,